A Safe Overtaking Control Scheme for Autonomous Vehicles using Rapid-Exploration Random Tree

Yincong Ma, Kit Guan Lim, M. K. Tan, H. S. Chuo, L. Angeline, K. Teo
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Abstract

In order to enhance the commuting ability of autonomous vehicles on the road and ensure the comfort and safety of passengers, the Rapid-exploration Random Tree (RRT) algorithm is applied to the research of safe overtaking control of autonomous vehicles. Firstly, the kinematics and dynamic model of the vehicle are implemented. Secondly, the RRT algorithm and the A-star algorithm are expounded, and the idea of the A-star algorithm is applied to the RRT algorithm for improvement. The improved algorithm is used to obtain the rough obstacle avoidance of the vehicle. The rough path is optimized by applying the cubic spline interpolation method to solve the problem that the path cannot be applied to the actual vehicle driving task. Finally, the simulation of the overtaking scheme is carried out. The results reveal that the safe overtaking scheme based on RRT algorithm achieves the predetermined requirements in the two actual cases under the premise of ensuring safety, controlling the swing of the sideslip angle of the vehicle's center of mass within a reasonable range. It has certain practical significance for ensuring the road safety of autonomous vehicles.
基于快速探索随机树的自动驾驶汽车安全超车控制方案
为了增强自动驾驶汽车在道路上的通勤能力,保证乘客的舒适性和安全性,将快速探索随机树(RRT)算法应用于自动驾驶汽车的安全超车控制研究。首先,建立了车辆的运动学和动力学模型。其次,阐述了RRT算法和A-star算法,并将A-star算法的思想应用到RRT算法中进行改进。将改进算法用于车辆的粗避障。采用三次样条插值方法对粗糙路径进行优化,解决了粗糙路径不能应用于实际车辆驾驶任务的问题。最后,对超车方案进行了仿真。结果表明,基于RRT算法的安全超车方案在保证安全的前提下,将车辆质心侧滑角的摆动控制在合理范围内,达到了两种实际情况下的预定要求。这对于保证自动驾驶汽车的道路安全具有一定的现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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